Progressive Image Transmission (PIT) is a general term for methods transmitting images, where the information contained in the image is transmitted in such a manner that the quality of the image is gradually improved at the receiving end of the transmission system as more information is transmitted.
Progressive image transmission has been proposed as a part of image transmission systems using low capacity transmission channels, such as the public switched telephone network. The use of a PIT scheme provides a user with an interpretable image faster. This is for instance of interest when many images have to be seen but only a few are of real interest. Thus, the user can decide to reject an image at any time during the transmission and thereby save time by rejecting the not interesting images at an early stage. Large image databases such as those emerging in the medical environment are amongst those which would benefit from such a transmission scheme.
Hence, a demand for an algorithm having features making it useful in and suitable for progressive image coding has emerged. A method possible to use for progressive image coding is the Joint Photographers Expert Group (JPEG) algorithm. The progressive image coding is then achieved using the methods of spectral selection or successive approximation as described in for instance the documents, W. B. Pennebaker, J. T. Mitchell, "JPEG still image data compression standard", Van Nostrand Reinhold, New York, 1993, or in G. K. Wallace, "The JPEG still picture compression standard", Communication of the ACM, Vol. 34, No. 4, April 1988, pp. 121-132.
However, the use or the JPEG algorithm for PIT is associated with some disadvantages. The major disadvantage is the low visual quality during the first stages of the transmission, which mainly is due to blocking artefacts appearing at high compression ratios. Thus, it is common that much information needs to be transmitted in order for the receiver to be able to decide whether or not he/she is interested in the image transmitted.
Recently, segmented image coding (SIC) or region based coding (RBC) approaches have been used for progressive image transmission. Region based coding is a relatively new image compression technique, in which the image is divided into regions of slowly varying intensity. The contours separating different regions are described by means of chain codes, and the image intensity inside such a region is approximated with use of a linear combination of base functions. The contours and the region intensities are then transmitted via a channel in order to provide the receiver with an image.
The RBC based algorithms provide a much better visual quality than e.g. the JPEG algorithm at high compression ratios. The reason for this is the blocking artefacts visible at high compression ratios using the JPEG algorithm. However, at lower compression ratios the visual quality of the RBC based algorithms does not outperform the JPEG algorithm. Moreover, the computational complexity of RBC algorithms is significantly higher than for the JPEG algorithm, which also has the advantage of being commercially available at a comparably low cost.
Most of the present RBC methods, approximate the grey value within a region as a weighted sum of base functions, whereafter the coefficients obtained are quantized and coded. Such techniques are described in: M. Gilge, "Region-orientated transform coding (ROTC) of images", Proc. of ICASSP 90, Albuquerque, New Mexico, April 1990, pp. 2245-2248, and M. Kunt, M. Benard, R. Leonard "Recent results in high compression image coding", IEEE Trans. circuits and systems, Vol. 34, November 1987, pp. 1306-1336.
In more recent RBC based approaches, the basis functions within a given region are orthonormal. The use of orthonormal functions makes it possible to obtain the coefficients of the linear expression independently, with fewer and numerically stable computations. See for instance W. Philips, C. A. Christopoulos, "Fast segmented image coding using weakly separable bases", Proc. of ICASSP 94, Adelaide, Australia, Apr. 19-22, 1994, Vol. V, pp.345-348. However, RBC algorithms have significant computational and memory requirements. This is due to that the orthonormal bases depend on the shape and size of a region and thus new individual bases functions must be computed for each region.
Furthermore, at low compression ratios, RBC does not offer better visual quality than JPEG. Thus, the RBC based algorithms lose their advantage compared to other compression algorithms at lower compression ratios.